Fast Nonnegative Tensor Factorizations with Tensor Train Model

被引:1
|
作者
Shcherbakova, E. M. [1 ]
Tyrtyshnikov, E. E. [2 ]
机构
[1] Lomonosov Moscow State Univ, Moscow 119991, Russia
[2] Russian Acad Sci, Marchuk Inst Numer Math, Moscow 119333, Russia
关键词
nonnegative tensor factorization; tensor train; Tucker decomposition; canonical decomposition; DECOMPOSITIONS;
D O I
10.1134/S1995080222070228
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Tensor train model is a low-rank approximation for multidimensional data. In this article we demonstrate how it can be succesfully used for fast computation of nonnegative tensor train, nonnegative canonical and nonnegative Tucker factorizations. The proposed approaches can be incorporated in wide range of methods to solve big data problems.
引用
收藏
页码:882 / 894
页数:13
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